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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM53143
Volume:
9 |
10 |
Oct 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Students often struggle with time management. This leads to last-minute studying, missed deadlines, and increased stress. Current study planning tools are usually fixed and do not adjust to a student’s changing performance, learning style, or schedule. To solve these issues, we propose an AI-power dynamic study management system.. This system generates personalized study schedules, automatically summarizes study materials using Natural Language Processing (NLP), and creates adaptive quizzes to support learning. It uses a mix of machine learning and reinforcement learning to analyze performance data, prioritize topics, and modify study plans based on quiz results, upcoming deadlines, and identified knowledge gaps. By offering clear recommendations and real-time adjustments, this solution aims to improve academic efficiency, enhance knowledge retention, and lower study-related stress, providing a powerful tool for modern education.
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Publication Date
10/21/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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